---
library_name: transformers
license: mit
base_model: almanach/camembert-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: trainer_output
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# trainer_output

This model is a fine-tuned version of [almanach/camembert-base](https://huggingface.co/almanach/camembert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2064
- Accuracy: 0.9119

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 30   | 0.3752          | 0.8742   |
| No log        | 2.0   | 60   | 0.3463          | 0.8742   |
| No log        | 3.0   | 90   | 0.2804          | 0.8742   |
| No log        | 4.0   | 120  | 0.2925          | 0.8805   |
| No log        | 5.0   | 150  | 0.2599          | 0.8868   |
| No log        | 6.0   | 180  | 0.2527          | 0.8931   |
| No log        | 7.0   | 210  | 0.2176          | 0.8994   |
| No log        | 8.0   | 240  | 0.2105          | 0.8994   |
| No log        | 9.0   | 270  | 0.2096          | 0.9119   |
| No log        | 10.0  | 300  | 0.2064          | 0.9119   |


### Framework versions

- Transformers 5.5.3
- Pytorch 2.7.0+cu126
- Datasets 4.8.4
- Tokenizers 0.22.2